1. Technical Field
The present invention relates to a method for solving the coverage of sensor nodes, and more particularly, to a method for selecting sensor nodes, in which the sensor nodes having best sensing coverage can be selected by way of determining a coverage level of the objects made by the sensor nodes and calculating the value of a contribution function for the objects contributed by the sensor nodes
2. Description of Related Art
Wireless sensor network consists of a plurality of sensor nodes, in which, each sensor node is responsible for collecting, processing, and storing the environment data. Moreover, the sensor node can communicate with any adjacent sensor node. Since the sensor node of wireless sensor network has the above properties, it can be applied to many environmental sensing applications, such as video surveillance system, radiation sensing, and biochemistry sensing, etc.
However, the wireless sensor network has a foundation problem that is coverage problem. The coverage problem means a condition of a filed or an object that a sensor can monitor it; Moreover, with different monitoring environments, the wireless sensor network needs to deal with different coverage problems. So that, when we want to deploy the wireless sensor network in a particular environment, the coverage problem must be considered in advance. For instance, when the wireless sensor network is used for monitoring an art gallery, it is the classical coverage problem in the wireless sensor network, called art gallery problem (the art gallery problem is introduced in reference 1: O'Rourke, J. “Art Gallery Theorems and Algorithms”, Oxford University Press, New York, 1987).
In addition to the coverage problem, the disposing points and the sensing directions of the sensor nodes are also the important considerations when we want to use the wireless sensor network to monitor a particular environment area. Please refer to FIG. 1, which illustrates the schematic view of a conventional surveillance system with wireless sensor network, as shown in FIG. 1, when an object O′ enters the covering range of the wireless sensor network, the surveillance ranges of three surveillance devices S1′, S2′, and S3′ fully cover the object O′. Please simultaneously refer to FIG. 2, which shows the image diagram of the object captured by these surveillance devices. As shown in FIG. 2, P1′, P2′, and P3′ are the object images of the object O′ captured by the surveillance device S1′, S2′, and S3′, respectively. Obviously, The covering ranges of three surveillance devices S1′, S2′, and S3′ fully cover the object O′, however, the images captured by the three surveillance devices can not facilitate people recognize the identification of the object O′.
Please refer to FIG. 3 and FIG. 4, which illustrate another schematic view of the conventional surveillance system with wireless sensor network and its image diagram of the object captured by the surveillance device, respectively. As shown in FIG. 3, based on the three surveillance devices S1′, S2′, and S3′ fully cover the object O′, the three surveillance devices S1′, S2′, and S3′ are respectively disposed and two adjacent surveillance devices have a particular included angle, so as to make the three surveillance devices S1′, S2′, and S3′ be able to capture the back, the left side, and the right side of the object O′, so that people can recognize the identification of the object O′ easily, as shown in FIG. 4.
Thus, through above descriptions, it is able to know that, when we want to use the wireless sensor network to monitor or sense a particular region, we should consider not only the coverage problem but also the disposing points and the sensing directions of sensor nodes. So, the wireless sensor network may perform the best monitoring/sensing efficiency.
Accordingly, based on the above reasons, the inventor of the present application has made great efforts to make inventive research thereon and eventually provided a method for selecting sensor nodes, so as to facilitate the wireless sensor network perform the best efficiency when it is applied to monitor or sense the particular environment.